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AAlbert1
By Level 7 Flexeran
Level 7 Flexeran

Synopsis: 


This article discusses the eligibility of file evidence submitted by customers that can be accepted into the ARL for processing. With huge submissions of file evidence, it has necessitated a discussion of filtering evidence of most value while maintaining a high level of quality expected in the ARL. 

 

Discussion: 

 

Adding large volumes of file evidence to the ARL does not contribute to enhancing the quality of the data, unless the file confirms the recognition of important applications (commercial) or allows you to track usage.  
Unfortunately, we are not able to manage large batches of unrecognized file evidence exported from the ‘unrecognized file evidence’ tab. These requests create intensive work and are not conducive to the ARL quality and inventory import performance. 
The main objective with unrecognized file evidence is not in clearing them from the unrecognized tab, but in filtering out the evidence of most value to your environment and adding those to our library. The remaining evidence in the unrecognized tab will not impact consumption or recognition on the device. This streamlines our file evidence list and facilitates better usage calculation and recognition.   

We are interested in working with ‘qualified’ file evidence that is filtered and vetted by you and your team to be useful in tracking usage (along with the commercial application the file allows to recognize).We would also consider the ‘proven to useless’ file evidence that can be validated as ignored by Flexera. A similar approach has recently been adapted for the Unix distribution (unlicensed) files. Overall, we wish to pursue the file evidence submissions on a more focused target with you. 
To better focus on file evidence of most value, we would suggest you filter and then export your unrecognized evidence on two basic conditions:  

  • Evidence data that contains all basic attribute details like file Name, Publisher/Company, Product, Version, File path, Type, Matches. 
     
  • Important file evidence that you know to be used in calculating usage or in some cases enable recognition for applications ( Ex: Java .exe files, UNIX files that have no extension). Some of the file evidence that we classify as ‘Qualified’ evidence contain the following file paths -  
    exe, .sys, .sys2, .cmptag, .swtag, .swidtag, dtag and .msi.  

 

Any significant changes to these criteria will be communicated in advance through Content notifications in the Flexera Community. Once we cover the most important file evidence, we can analyse the remaining evidence you have in your environment and determine the importance in processing and adding them to the ARL. 

We work to continually improve the quality of evidence in FlexNet Manager, and a large part of that is the importance of the Flexera community. We have thousands of customers participating regularly in discussions that involve updates and changes to Flexera product and content.  
This helps other customers new to the environment or working on similar topics to better understand our process. This also helps us update our content libraries based on customer input. We strongly recommend leveraging the Flexera community to better understand the scale of file evidence that will be of consequence to your environment.  

For further details on this issue and a larger context to the task of managing evidence in Flexera, we have an important seminar conducted by our Product Manager Nicolas Rousseau that you can find here 

 

Going Forward: 

While we aim to reduce the task of processing large batches of evidence, we are simultaneously focusing on qualitative methods to reduce the impact and presence of unrecognized evidence in the Flexera UI. One method of pursuing this is for us to work on specific scripts that will only filter on evidence of most prevalence in your environment and look to publish a list of file evidence that is required for usage/recognition on that device. This is currently a project in its early stages of development and will be worked on as we expand our evidence quality capabilities.  

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